Package: simtrial 0.4.2

Yujie Zhao

simtrial: Clinical Trial Simulation

Provides some basic routines for simulating a clinical trial. The primary intent is to provide some tools to generate trial simulations for trials with time to event outcomes. Piecewise exponential failure rates and piecewise constant enrollment rates are the underlying mechanism used to simulate a broad range of scenarios such as those presented in Lin et al. (2020) <doi:10.1080/19466315.2019.1697738>. However, the basic generation of data is done using pipes to allow maximum flexibility for users to meet different needs.

Authors:Keaven Anderson [aut], Yujie Zhao [ctb, cre], John Blischak [ctb], Nan Xiao [ctb], Yilong Zhang [aut], Jianxiao Yang [ctb], Lili Ling [ctb], Xintong Li [ctb], Ruixue Wang [ctb], Yi Cui [ctb], Ping Yang [ctb], Yalin Zhu [ctb], Heng Zhou [ctb], Amin Shirazi [ctb], Cole Manschot [ctb], Merck & Co., Inc., Rahway, NJ, USA and its affiliates [cph]

simtrial_0.4.2.tar.gz
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simtrial_0.4.2.tar.gz(r-4.5-noble)simtrial_0.4.2.tar.gz(r-4.4-noble)
simtrial_0.4.2.tgz(r-4.4-emscripten)simtrial_0.4.2.tgz(r-4.3-emscripten)
simtrial.pdf |simtrial.html✨
simtrial/json (API)
NEWS

# Install 'simtrial' in R:
install.packages('simtrial', repos = c('https://merck.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/merck/simtrial/issues

Pkgdown site:https://merck.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • ex1_delayed_effect - Time-to-event data example 1 for non-proportional hazards working group
  • ex2_delayed_effect - Time-to-event data example 2 for non-proportional hazards working group
  • ex3_cure_with_ph - Time-to-event data example 3 for non-proportional hazards working group
  • ex4_belly - Time-to-event data example 4 for non-proportional hazards working group
  • ex5_widening - Time-to-event data example 5 for non-proportional hazards working group
  • ex6_crossing - Time-to-event data example 6 for non-proportional hazards working group
  • mb_delayed_effect - Simulated survival dataset with delayed treatment effect

On CRAN:

Conda:

cpp

9.30 score 21 stars 52 scripts 619 downloads 24 exports 16 dependencies

Last updated 2 hours agofrom:0765c811ec. Checks:12 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 25 2025
R-4.5-win-x86_64OKMar 25 2025
R-4.5-mac-x86_64OKMar 25 2025
R-4.5-mac-aarch64OKMar 25 2025
R-4.5-linux-x86_64OKMar 25 2025
R-4.4-win-x86_64OKMar 25 2025
R-4.4-mac-x86_64OKMar 25 2025
R-4.4-mac-aarch64OKMar 25 2025
R-4.4-linux-x86_64OKMar 25 2025
R-4.3-win-x86_64OKMar 25 2025
R-4.3-mac-x86_64OKMar 25 2025
R-4.3-mac-aarch64OKMar 25 2025

Exports:as_gtcounting_processcreate_cutcreate_testcut_data_by_datecut_data_by_eventearly_zerofhfit_pwexpget_analysis_dateget_cut_date_by_eventmaxcombombmilestonemultitestrandomize_by_fixed_blockrmstrpwexprpwexp_enrollsim_fixed_nsim_gs_nsim_pw_survto_sim_pw_survwlr

Dependencies:codetoolsdata.tabledigestdoFutureforeachfuturefuture.applyglobalsiteratorslatticelistenvMatrixmvtnormparallellyRcppsurvival

Approximating an arbitrary hazard function

Keaven Anderson

Rendered fromarbitrary-hazard.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2024-05-07
Started: 2023-11-28

Basic tools for time-to-event trial simulation and testing

Keaven Anderson

Rendered fromroutines.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2024-05-07
Started: 2023-11-28

Computing p-values for Fleming-Harrington weighted logrank tests and the MaxCombo test

Keaven Anderson, Yujie Zhao

Rendered frommaxcombo.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2024-05-07
Started: 2024-04-11

Custom Fixed Design Simulations: A Tutorial on Writing Code from the Ground Up

Yujie Zhao and Keaven Anderson

Rendered fromsim_fixed_design_custom.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2025-03-25
Started: 2025-03-21

Note on potential discrepancies between simtrial and survdiff

Larry Leon

Rendered fromdiscrepancy-between-simtrial-and-survival.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2025-03-13
Started: 2025-01-31

Restricted mean survival time (RMST)

Yujie Zhao, Yilong Zhang

Rendered fromrmst.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2024-07-23
Started: 2024-02-05

Simulate Fixed Designs with Ease via sim_fixed_n

Yujie Zhao and Keaven Anderson

Rendered fromsim_fixed_design_simple.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2025-03-21
Started: 2025-03-21

Simulate Group Sequential Designs with Ease via sim_gs_n

Yujie Zhao and Keaven Anderson

Rendered fromsim_gs_design_simple.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2025-03-21
Started: 2025-03-21

Simulating time-to-event trials in parallel

Cole Manschot, Nan Xiao

Rendered fromparallel.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2024-08-08
Started: 2023-09-25

TTE simulation data manipulations

Keaven Anderson

Rendered fromworkflow.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2024-08-08
Started: 2023-05-30

Using the Magirr-Burman weights for testing

Keaven Anderson, Yujie Zhao

Rendered frommodest-wlrt.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2024-08-08
Started: 2023-11-28

Readme and manuals

Help Manual

Help pageTopics
Convert summary table to a gt objectas_gt as_gt.simtrial_gs_wlr
Process survival data into counting process formatcounting_process
Create a cutting functioncreate_cut
Create a cutting test functioncreate_test
Cut a dataset for analysis at a specified datecut_data_by_date
Cut a dataset for analysis at a specified event countcut_data_by_event
Zero early weighting functionearly_zero
Time-to-event data example 1 for non-proportional hazards working groupex1_delayed_effect
Time-to-event data example 2 for non-proportional hazards working groupex2_delayed_effect
Time-to-event data example 3 for non-proportional hazards working groupex3_cure_with_ph
Time-to-event data example 4 for non-proportional hazards working groupex4_belly
Time-to-event data example 5 for non-proportional hazards working groupex5_widening
Time-to-event data example 6 for non-proportional hazards working groupex6_crossing
Fleming-Harrington weighting functionfh
Piecewise exponential survival estimationfit_pwexp
Derive analysis date for interim/final analysis given multiple conditionsget_analysis_date
Get date at which an event count is reachedget_cut_date_by_event
MaxCombo testmaxcombo
Magirr and Burman weighting functionmb
Simulated survival dataset with delayed treatment effectmb_delayed_effect
Milestone test for two survival curvesmilestone
Perform multiple tests on trial data cuttingmultitest
Permuted fixed block randomizationrandomize_by_fixed_block
RMST difference of 2 armsrmst
The piecewise exponential distributionrpwexp
Generate piecewise exponential enrollmentrpwexp_enroll
Simulation of fixed sample size design for time-to-event endpointsim_fixed_n
Simulate group sequential designs with fixed sample sizesim_gs_n
Simulate a stratified time-to-event outcome randomized trialsim_pw_surv
Summary of group sequential simulations.summary.simtrial_gs_wlr
Convert enrollment and failure rates from 'sim_fixed_n()' to 'sim_pw_surv()' formatto_sim_pw_surv
Weighted logrank testwlr wlr.counting_process wlr.tte_data